Atmospheric sensor network and analytical information system related thereto

ABSTRACT

Disclosed is an atmospheric information network comprised of a group of low earth orbit satellite-based sensors providing global coverage of the earth, together with one or more ground-based sensor networks, together with one or more mobile sensor networks, all operating to collect near-real-time or real-time data, together with data gathering from other governmental and commercial atmospheric data sources, together with software algorithms and processes for data reduction, data analysis, correlation of information, data fusion, modeling, reporting of near-real-time real-time atmospheric conditions of air pollution and wind, and prediction of future atmospheric conditions of air pollution and wind. Such information is presented in geospatial and infographic formats on computer or mobile device displays, or electronic billboards.

This application includes material that is subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent disclosure, as it appears in thePatent and Trademark Office files or records, but otherwise reserves allcopyright rights whatsoever.

CROSS-REFERENCE TO RELATED APPLICATIONS

N/A.

TECHNICAL FIELD

The present invention relates in general to the field of sensing anddata analysis. In particular, the present invention relates to acomputerized automated data fusion, atmospheric modeling and predictionof atmospheric chemistry and wind processes, with emphasis on airpollution, and effects of air pollution on health.

STATEMENT OF FEDERALLY FUNDED RESEARCH

None.

BACKGROUND OF THE DISCLOSURE

Air pollution is a 3-dimensional (3D) dynamic process in the globalatmospheric system. Considerable air pollution data exists today,collected by many Earth-Observing agencies, but, the ability to deriveactionable information from it is limited due to multiple factorsincluding (i) fragmented, patchy terrestrial networks and limitedspace-based monitoring which see mostly narrow slices of atmosphere,(ii) data flow from point of observation to end-user typically does nothappen on a real-time or near real-time basis, (iii) data is captured ina “snapshot” format, or a mostly two dimensional (2D) approach whichconstrains the ability to understand air pollution movement and suchdesirable aspects as tracing air pollution back to its source(s).

Several other factors inhibit the ability to create actionable airpollution information including the fact that most existing data issegmented, hard to access, typically formatted for science research andbroad data integration has not been achieved. Specifically, integrationof historical data with real time data is not yet generally available;integration of such information with predictive analytical models is notyet generally available, and; integration of air pollution data withcorresponding wind data is not yet generally available. In addition,only pedestrian approaches to visualizing the data are being taken whichgreatly limits insight generation. Contrast the latter with taking astrategic visualization approach which tailors information presentationto the specific needs of the audience/customer and captivates.

The U.S. Environmental Protection Agency (HPA), the European EnvironmentAgency (EEA), and the Chinese government are among the main driversbehind existing terrestrial networks. Outside of the U.S. and Europe,very little reliable terrestrial network monitoring exists. Theterrestrial-based air quality surveillance system in the U.S. consistsof a network of monitoring stations designated as “SLAMS”, “NAMS”, and“PAMS”, SLAMS, or State and Local Air Monitoring Stations, measureambient concentrations of pollutants (for which standards have beenestablished). NAMS, or National Air Monitoring Stations, are a subset ofSLAMS, and are urban area long-term air monitoring networks that prose asystematic, consistent database for air quality comparisons and trendsanalysis. These sites must meet more stringent siting, equipment type,and qualify assurance criteria. PAMS, or Photochemical MonitoringStations, are also a subset of SLAMS, and monitor volatile organiccompounds as ozone precursors during the summer ozone season.

A range of satellites exist today with air pollution data gatheringcapabilities; including, for example, Terra, Aqua, Aura. MetOp and GOES.The payloads measure certain aspects of air pollution over certain areasof the U.S. and Europe. With their mostly low-earth-orbit designs, datamonitoring occurs more on a daily basis versus hourly. Data feeds fromthese satellites are not proactively fused with respective in-countryterrestrial networks. It is therefore a critical need to efficientlyensure the collection of near-real-time or real-time data, together withdata gathering from other governmental and commercial atmospheric datasources which aggregate such sources of information. Given the above, acomprehensive approach that integrates, synthesizes and innovates isrequired to appropriately address the air pollution informationopportunity. This is a cost-driven opportunity comprised of hundreds ofbillions of dollars lost annually in such areas as health care andagriculture.

SUMMARY OF THE DISCLOSURE

The present invention provides an atmospheric information networkintended to provide real-time or near-real-time air pollutioninformation, fused with wind and weather information to end users oncomputers and mobile devices. The system is comprised, in part, of agroup (“constellation”) of low earth orbit satellite-based sensorsproviding global coverage of the earth, together with one or moreground-based sensor networks, together with one or more mobile sensornetworks, all operating to collect near-real-time or real-time data. Thesystem of the present invention further obtains data from governmental,non-governmental, third-party and commercial atmospheric data sources,and performs data fusion operations on data from all such sources toprovide enhanced information. Such governmental, non-governmental,third-party and commercial data sources may be satellite-based, orground-based, or marine/mobile-based, or automotive mobile-based, orend-user hand-held-device mobile-based, or any combination of these.

The system of the present invention further comprises, in part,processes for data reduction, data analysis, correlation of information,data fusion, modeling, reporting of near-real-time or real-timeatmospheric conditions of air pollution and wind, and prediction offuture atmospheric conditions of air pollution and wind. It is anobjective of the present invention to provide a global atmospheric modelon a regular periodic basis, incorporating the air pollutioninformation, wind information, and available weather information,gathered from all sources, to create a global picture of air pollutionand related atmospheric conditions. The global model may be run in asingle processing operation, or may be broken into parts based onregions of the earth or based on other partitioning criteria, and ran inparallel or sequential processes in the system's own computingfacilities. Alternatively the periodic computation of the model may berun in external computing services provided to the system. Resultinginformation is presented in geospatial and infographic formats oncomputer or mobile device displays.

The multilateral data sources support multiple feedback pathways,dynamic information updates and information quality improvements basedon opportunistically sensed local conditions. The resulting informationis further subject to interpretation by means of software algorithms,with presentation of situational awareness information and actionableadvisory services to end users.

The system of the present invention is further comprised, in part, ofend-users, collectively referred to as a user community. Members of theuser community may optionally provide individual health information inthe form of health profile data, which are stored in the storage modulesof the system of the present invention. Advisories to such end-user aretailored based on relevance to individual end-user health information,providing configurable alert levels and context-sensitive information.

Moreover, users who carry mobile platforms which carry air pollutionsensors on-board and are capable of transmitting such data to the systemmay contribute such sensed air pollution information into the system.Such data is incorporated into the periodic update of the global model.

These and other features of the present invention will become readilyapparent upon further review of the following specification and figures.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of thedisclosure will be apparent from the following description ofembodiments as illustrated in the accompanying drawings, in whichreference characters refer to the same parts throughout the variousviews. The drawings are not necessarily to scale, emphasis instead beingplaced upon illustrating principles of the disclosure:

FIG. 1 depicts a system diagram of the major components and data flowsof the system.

FIG. 2 depicts a notional depiction of the satellite constellation as adata-collection network.

FIG. 3 depicts a notional depiction of a satellite with dual sensorpackages and ground tracking.

FIG. 4 depicts a notional depiction of a satellite with dual sensorpackages and ground tracking, alternative configuration.

FIG. 5 depicts a notional depiction of satellite sensor data retrievalpathway.

FIG. 6 depicts a notional illustration of a ground sensor stationpackage.

FIG. 7 depicts a notional illustration of an alternative ground sensorstation package.

FIG. 8 depicts a notional depiction of the ground-based data-collectionnetwork topology.

FIG. 9 depicts variable-density sensor grid deployments in ground-basedsensor network.

FIG. 10 depicts a schematic view of data reduction, analysis, and datafusion.

FIG. 11 depicts a schematic view of information presentation.

DETAILED DESCRIPTION OF THE DISCLOSURE

While the making and using of various embodiments of the presentinvention are discussed in detail below, it should be appreciated thatthe present invention provides many applicable inventive concepts thatcan be embodied in a wide variety of specific contexts The specificembodiments discussed herein are merely illustrative of specific ways tomake and use the disclosure and do not delimit the scope of thedisclosure.

All publications and patent applications mentioned in the specificationare indicative of the level of skill of those skilled in the art towhich this disclosure pertains. All publications and patent applicationsare herein incorporated by reference to the same extent as if eachindividual publication or patent application was specifically andindividually indicated to be incorporated by reference.

The present invention will now be described more fully hereinafter withreference to the accompanying figures and drawings, which form a parthereof, and which show, by way of illustration, specific exampleembodiments. Subject matter may, however, be embodied in a variety ofdifferent forms and, therefore, covered or claimed subject matter isintended to be construed as not being limited to any example embodimentsset forth herein, example embodiments are provided merely to beillustrative. Likewise, a reasonably broad scope for claimed or coveredsubject matter is intended. Among other things, for example, subjectmatter may be embodied as methods, devices, components, or systems. Thefollowing detailed description is, therefore, not intended to be takenin a limiting sense

Throughout the specification and claims, terms may have nuance meaningssuggested or implied in context beyond an explicitly stated meaning.Likewise, the phrase “in one embodiment” as used herein does notnecessarily refer to the same embodiment and the phrase “in anotherembodiment” as used herein does not necessarily refer to a differentembodiment. It is intended, for example, that claimed subject matterinclude combinations of example embodiments in whole or in pan.

In general, terminology may be understood at least in part from usage incontext. For example, terms, such as “and”, “or”, or “and/or,” as usedherein may include a variety of meanings that may depend at least inpart upon the context in which such terms are used. Typically, “or” ifused to associate a list, such as A, B or C, is intended to mean A, B,and C, here used in the inclusive sense, as well as A, B or C, here usedin the exclusive sense. In addition, the term “one or more” as usedherein, depending at least in part upon context, may be used to describeany feature, structure, or characteristic in a singular sense or may beused to describe combinations of features, structures or characteristicsin a plural sense. Similarly, terms, such as “a,” “an,” or “the,” again,may be understood to convey a singular usage or to convey a pluralusage, depending at least in part upon context. In addition, the term“based on” may be understood as not necessarily intended to convey anexclusive set of factors and may, instead, allow for existence ofadditional factors not necessarily expressly described, again, dependingat least in part on context.

The present invention is described below with reference to flow chartsand operational illustrations of methods and devices. It is understoodthat each block of the block diagrams or operational illustrations, andcombinations of blocks in the block diagrams or operationalillustrations, can be implemented by means of analog or digital hardwareand computer program instructions. These computer program instructionscan be provided to a processor of a general purpose computer, specialpurpose computer, ASIC, or other programmable data processing apparatus,such that the instructions, which execute via the processor of thecomputer or other programmable data processing apparatus, implement thefunctions/acts specified in the system flow chart or operational blockor blocks. In some alternate implementations, the functions/acts notedin the blocks can occur out of the order noted in the operationalillustrations. For example, two blocks shown in succession can in factbe executed substantially concurrently or the blocks can sometimes beexecuted in the reverse order, depending upon the functionality/actsinvolved.

For the purposes of this disclosure a computer readable medium (orcomputer-readable storage medium/media) stores computer data, which datacan include computer program code (or computer-executable instructions)that is executable by a computer, in machine readable form. By way ofexample, and not limitation, a computer readable medium may comprisecomputer readable storage media, for tangible or fixed storage of data,or communication media for transient interpretation of code-containingsignals. Computer readable storage media, as used herein, refers tophysical or tangible storage (as opposed to signals) and includeswithout limitation volatile and non-volatile, removable andnon-removable media implemented in any method or technology for thetangible storage of information such as computer-readable instructions,data structures, program modules or other data. Computer readablestorage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM,flash memory or other solid state memory technology, CD-ROM, DVD, orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other physical ormaterial medium which can be used to tangibly store the desiredinformation or data or instructions and which can be accessed by acomputer or processor.

For the purposes of this disclosure the term server should be understoodto refer to a service point which provides processing, database, andcommunication facilities. By way of example, and not limitation, theterm server can refer to a single, physical processor with associatedcommunications and data storage and database facilities, or it can referto a networked or clustered complex of processors and associated networkand storage devices, as well as operating software and one or moredatabase systems and application software that support the servicesprovided by the server. Servers may vary widely in configuration orcapabilities, but generally a server may include one or more centralprocessing units and memory. A server may also include one or more massstorage devices, one or more power supplies, one or more wired orwireless network interfaces, one or more input/output interfaces, or oneor more operating systems, such as Windows Server, Mac OS X, Unix,Linux, FreeBSD, Android, Chrome OS, or the like.

For the purposes of this disclosure a network should be understood torefer to a network that may couple devices so that communications may beexchanged, such as between a server and a client device or other typesof devices, including between wireless devices coupled via a wirelessnetwork, for example. A network may also include mass storage, such asnetwork attached storage (NAS), a storage area network (SAN), or otherforms of computer or machine readable media, for example. A network mayinclude the Internet, one or more local area networks (LANs), one ormore wide area networks (WANs), wire-line type connections, wirelesstype connections, cellular or any combination thereof. Likewise,sub-networks, which may employ differing architectures or may becompliant or compatible with differing protocols, may interoperatewithin a larger network. Various types of devices may, for example, bemade available to provide an interoperable capability for differingarchitectures or protocols. As one illustrative example, a router mayprovide a link between otherwise separate and independent LANs.

A communication link or channel may include, for example, analogtelephone lines, such as a twisted wire pair, a coaxial cable, full orfractional digital lines including T1, T2, T3, or T4 type lines.Integrated Services Digital Networks (ISDNs), Digital Subscriber Lines(DSLs), Fiber-optic networks, wireless links including satellite links,or other communication links or channels, such as may be known to thoseskilled in the art. Furthermore, a computing device or other relatedelectronic devices may be remotely coupled to a network, such as via atelephone line or link, for example.

For purposes of this disclosure, a “wireless network” should beunderstood to couple client devices with a network using some form ofradio communications. A wireless network may employ stand-alone ad-hocnetworks, mesh networks, Wireless LAN (WLAN) networks, cellularnetworks, or the like. A wireless network may further include a systemof terminals, gateways, routers, or the like coupled by wireless radiolinks, or the like, which may move freely, randomly or organizethemselves arbitrarily, such that network topology may change, at timeseven rapidly. A wireless network may further employ a plurality ofnetwork access technologies, including Long Term Evolution (LTE), WLAN,Wireless Router (WR) mesh, or 2nd, 3rd, or 4th generation (2G, 3G, or4G) cellular technology, or the like. Network access technologies mayenable wide area coverage for devices, such as client devices withvarying degrees of mobility, for example.

For example, a network may enable radio frequency (RF) or wireless typecommunication via one or more network access technologies, such asGlobal System for Mobile communication (GSM), Universal MobileTelecommunications System (UMTS), General Racket Radio Services (GPRS),Enhanced Data GSM Environment (EDGE), 3GPP Long Term Evolution (LTE),LTE Advanced, Wideband Code Division Multiple Access (WCDMA), Bluetooth,802.11b/g/n, or the like. A wireless network may Include virtually anytype of wireless communication mechanism by which signals may becommunicated between devices, such as a client device or a computingdevice, between or within a network, or the like.

A computing device may be capable of sending or receiving signals, suchas via a wired or wireless network, or may be capable of processing orstoring signals, such as in memory as physical memory states, and may,therefore, operate as a server. Thus, devices capable of operating as aserver may include, as examples, dedicated rack-mounted servers, desktopcomputers, laptop computers, set top boxes, integrated devices combiningvarious features, such as two or more features of the foregoing devices,or the like. Servers may vary widely in configuration or capabilities,but generally a server may include one or more central processing unitsand memory. A server may also include one or more mass storage devices,one or more power supplies, one or more wired or wireless networkinterfaces, one or more input/output interfaces, or one or moreoperating systems, such as Windows Server, Mac OS X, Unix, Linux,FreeBSD, Android, Chrome OS, or the like.

For purposes of this disclosure, a monitoring (or sensor or user) devicemay include an instrument such as a sensor, which may further includeone or more computing devices capable of sending or receiving signals,such as via a wired or a wireless network A monitoring device may, forexample, include a desktop computer or a portable device, such as acellular telephone, a smart phone, a display pager, a radio frequency(RF) device, an infrared (IR) device an Near Field Communication (NFC)device, a Personal Digital Assistant (PDA), a handheld computer, atablet computer, a laptop computer, phablets, intelligent clothing a settop box, a wearable computer, an integrated device combining variousfeatures, such as features of the forgoing devices, or the like.

A monitoring device may vary in terms of capabilities or featuresClaimed subject matter is intended to cover a wide range of potentialvariations. For example, a device may include a numeric keypad or adisplay of limited functionality, such as a monochrome liquid crystaldisplay (LCD) for displaying text. In contrast, however, as anotherexample a web-enabled monitoring device may include one or more physicalor virtual keyboards, mass storage, one or more gas sensors,thermometers, barometers, fire detectors, accelerometers, one or moregyroscopes, global positioning system (GPS) or otherlocation-identifying type capability, or a display with a high degree offunctionality, such as a touch-sensitive color 2D or 3D display, forexample.

A monitoring device may include or may execute a variety of operatingsystems, including a personal computer operating system, such as aWindows, iOS or Linux, or a mobile operating system, such as iOS,Android, Chrome OS. or Windows Mobile, or the like. A monitoring devicemay include or may execute a variety of possible applications, such as asoftware application enabling communication with other devices, such ascommunicating one or more messages, such as via email, communicationlink, short message service (SMS), or multimedia message service (MMS),including via a network, such as a social network. A monitoring devicemay also include or execute an application to communicate content, suchas for example, textual content, multimedia content, or the like. Amonitoring device may also include or execute an application to performa variety of possible tasks, such as browsing, searching, displayingvarious forms of content, including locally stored or streamed video.The foregoing is provided to illustrate that claimed subject matter isintended to include a wide range of possible features or capabilities.

The principles described herein may be embodied in many different forms.The system of the present invention comprises a computing device andconfiguration software enabling the computing device to capture andstore information from isolated and various remote client devicesincluding atmospheric monitoring devices and indicators. The systemincludes a processor of the computer or other programmable dataprocessing apparatus that collects instrumentation data from a pluralityof monitoring instruments. Configuration software provides the means forcommunicating with a wide variety of disparate instrumentation systems.

Turning to FIGS. 1-11, illustrative embodiments of the system of thepresent invention are provided. The principal computer processor,server, or combination of devices that comprises hardware programmed inaccordance with the special purpose functions herein, referred to forconvenience as a programmable logic system, can include a networkmodule, programmable logic module, data extraction module, comparisonmodule, and results module for achieving data, correlation, sourcecorrelation, geospatial correlation, geospatial value surface mapping,wind and weather data correlation, forward-predictive global airpollution modeling, four-dimensional animation, health correlation,health-care information fusion, and the like. It should be understoodthat the engine(s) and modules discussed herein are non-exhaustive, asadditional or fewer engines and/or modules may be applicable to theembodiments of the systems and methods discussed. Specific programmingin a general computer includes the programmable logic module and resultsmodule for generating the data necessary for the functional aspects ofthe present invention. The process of the present invention may beperformed by the programmable logic system and focuses upon processingdata to effectuate the logic and sequential approach discussed herein.

Thus, in an exemplary embodiment of the present invention, a system isprovided for integrating a computing device into an instrumentation andcontrol system having a programmable logic system adapted for connectionto atmospheric sensors and equipment control devices, wherein thecomputing device is operabiy connected to the programmable logic system,the computing device having a processor, an area of main memory, andconfiguration software; operable by the processor when loaded into themain memory, the configuration software having means for reconfiguringthe programmable logic system to communicate with the atmosphericsensors and instrumentation control devices; and means for configuringalarms based on the input from the atmospheric sensors signalingpre-determined concentrations of hazardous air pollution components.

It is therefore an embodiment of the present invention to provide asystem comprised of a set of hardware components, together with a set ofsoftware components, together with data receipt and data deliveryprocesses, together with analytic and presentation processes, andtogether with information presentation software suitable for operationon conventional computer equipment as well as mobile computer equipment.An atmospheric information network comprised of a group(“constellation”) of low earth orbit satellite-based sensors providesglobal coverage of the earth, together with one or more ground-basedsensor networks, together with one or more mobile sensor networks, alloperating to collect near-real-time or real-time data, together withdata gathering from other governmental, non-governmental, third-partyand commercial atmospheric data sources, together with softwarealgorithms and processes for data reduction, data analysis, correlationof information, data fusion, modeling, reporting of near-real-time orreal-time atmospheric conditions of air pollution and wind, andprediction of future atmospheric conditions of air pollution and wind.Such information is presented in geospatial and infographic formats oncomputer or mobile device displays. The multilateral data sourcessupport multiple feedback pathways, dynamic information updates andinformation quality improvements based on opportunistically sensed localconditions. The resulting information is farther subject tointerpretation by means of software algorithms, with presentation ofsituational awareness information and actionable advisory services toend users. Such advisories can be further tailored based on relevance toindividual end-user health information, providing configurable alertlevels and context-sensitive information. Users who have providedindividuals health information profiles which are stored in the systemfor this purpose, and users who carry mobile platforms which carry airpollution sensors on-board and are capable of transmitting such data tothe system, comprise a user community.

In one embodiment, the present invention senses and collects real-timeand near-real-time global air pollution data, and correlates, analyzes,transforms, stores, and presents air pollution information based on suchdata, from sensor networks which are part of the system, as well asincorporating data from external databases and sensor networks operatedby others. In another embodiment, the system acts to utilize such datato provide end-users with actionable information and recommendationsbased in part on general human conditions as well as on specific healthprofiles of individual end users who have provide their healthinformation to the system for comparative use. A further embodiment ofthe system provides such air pollution information to externalgovernmental, non-governmental, third-party and commercial entitiesenabling them to integrate such information into their own presentationsystems and recommendation processes.

Another embodiment provides near-real-time global satellite-sourcedpollution data that is normalized, correlated with terrestrial pollutiondata and other data, personalized for an end-user and securely deliveredto a desktop or mobile device, optionally as a software applicationservice.

Still another embodiment provides near-real-time Global Satellitesourced pollution data with predictive forecast showing normalized,correlated, personalized or end-user specific data as a securebusiness-to-business service for smart nation integration and/orconsumer electronics integration.

Yet another embodiment of this disclosure provides a globalnear-real-time pollution data system which obtains data from aconstellation of satellite and ground station sensors and other sources,and delivers such data over a secure v6 network for commercialconsumption that is normalized, correlated and personalized as abusiness-to-business software application service for mobilecommunications devices.

There is also an embodiment providing a global near-real-time pollutiondata system which obtains data from a constellation of satellite andground station sensors and other sources, normalized, correlated andpersonalized as business-to-business software application service forinsurance data centers, corporate compliance, and national complianceagencies.

Embodiments disclosed herein also provide for a global near-real-timepollution data system which obtains data from a constellation ofsatellite and ground station sensors and other sources, normalized,correlated and displayed on airline schedule display boards in airports,providing destination air pollution:condition reports and predictions.

Additionally, an embodiment herein provides a global near-real-timepollution data system which obtains data from a constellation ofsatellite and ground station sensors and other sources, normalized,correlated and displayed in the context of urban roadway informationdisplays.

In another embodiment, a global near-real-time pollution data systemobtains data from a constellation of satellite and ground stationsensors and other sources, normalized, correlated and displayed in thecontext of weather information displays.

In yet another embodiment, a global near-real-time pollution data systemobtains data from a constellation of satellite and ground stationsensors and other sources including historical sources, that isnormalized, correlated and displayed in the context of real estateinformation maps.

Turning to FIG. 1, a satellite group (“constellation”) 105 ofLow-Earth-Orbit satellites comprised of eighteen to twenty-sixindividual satellites 100 serve as sensor platforms. Each satellitecarries a suite of air pollution sensors and measures a set ofhuman-relevant air pollution constituents in the atmosphere as it tracksacross the surface of the earth. In one embodiment of the system, eachsatellite also carries an optical or radio-frequency sounder to providethird-dimensional information. In another embodiment of the system, eachsatellite also carries a set of weather sensors to provide weatherinformation to complement external weather data sources. Thesesatellites provide complete or nearly complete geospatial coverage overthe surface of the earth, and temporal coverage such that each point onthe globe is revisited on a schedule rarely exceeding an hour.

Air pollution data is communicated to a database 160 configured to holduntransformed data (termed “L0 data”), and data which has beentransformed only once (termed “L1” data), hereinafter referred to as adatabase of L0 and L1 data.

The sensor instruments on the satellite constellation 105 are managed bymeans of the satellite sensor administration software 115 running on thesatellite sensor administration computer system 110. The satellitesensor administration software 115 transfers data 130 to and from adatabase 120 of calibration information and testing data, and transfers125 control signals and calibration adjustment instructions to and fromindividual satellites 100 to adjust and calibrate sensor functionality.

The system also transfers 168 air pollution data, wind and weather datafrom external sources held in external databases 155 associated withdata collection networks operated by governments, non-governmentalorganizations, third-party and commercial entities. These data are alsostored in the database of L0 and L1 data 160.

In an embodiment of the system, a network of ground-based sensorstations 135, and local data aggregation computer nodes 140 are deployedin selected locations in a network grid on or near the surface of theearth. These sensor stations collect local air pollution data, and thisdata is transferred 210 to the database of L0 and L1 data 160.

In another embodiment of the system, a network of mobile sensor stations275 is deployed on ocean-going vessels 270 worldwide. Air pollution datacollected by this network is transferred 280 to the database of L0 andL1 data 160, either through forwarding stations which are part of thesystem, or through forwarding data pathways operated by others.

In another embodiment of the system, a network of automotive mobilesensor stations 260 is deployed on motor vehicles 255. Air pollutiondata collected by this network is transferred 265 to the database of L0and L1 data 160, either through forwarding stations which are part, ofthe system, or through forwarding data pathways operated by others.

In another embodiment of the system, a network of mobile aeronauticalsensor stations 283 is deployed on aircraft 282. Air pollution datacollected by this network is transferred 284 to the database of L0 andL1 data 160, either through forwarding stations which are part of thesystem, or through forwarding data pathways operated by others.

In another embodiment of the system, a network of mobile aeronauticalsensor stations 287 is deployed on unmanned aircraft systems (so-calleddrones) 285. Air pollution data collected by this network is transferred288 to the database of L0 and L1 data 160, either through forwardingstations which are part of the system, or through forwarding datapathways operated by others.

In another embodiment of the system, a network of mobile aeronauticalsensor stations 291 is deployed on aircraft-like unmanned aircraftsystems (so-called drones) designed for long-duration flight 290. Airpollution data collected by this network is transferred 292 to thedatabase of L0 and L1 data 160, either through forwarding stations whichare part of the system, or through forwarding data pathways operatedhave others.

In another embodiment of the system, a network of mobile or tetheredaeronautical sensor stations 295 is deployed on balloon-like orlighter-than-air unmanned aircraft systems (so-called aerostat drones)designed for long-duration flight or station-keeping aloft 294. Airpollution data collected by this network is transferred 296 to thedatabase of L0 and L1 data 160, either through forwarding stations whichare part of the system, or through forwarding data pathways operated byothers.

The system processes air pollution data periodically on a regular cycle,as well as on an ad hoc basis. The analytic software module 165 ingests215 sets of L0 data or L1 data from the database of L0 and L1 data 160,and passes the data through a sequence of analytic steps. The results ofprocessing may include but are not limited to, presentable air pollutioninformation on individual parameters, geospatial correlations, temporalcorrelations, correlations with wind data and other weather processes,incorporation into atmospheric models, forward predictions, informationbased on synergistic discovery of information patterns, and actionablerecommendations. The results of the model processing are validated fromtime to time against a known set of conditions and outcome. The resultsof processing are transferred 220 into a database of analyzedinformation 170, where the information is stored.

Stored air pollution information and other information in the databaseof analyzed information 170 are transferred into a presentation softwaremodule 175. The presentation module may pass the information onward 250on a bulk basis through an application programming interface (“API”) toanother entity, such as, for example, a commercial customer, for itsuse. The presentation software module 175 may alternatively pass theinformation to a presentation browser-based Web-application 185displayed in an end-user stationary computer 180, conventionaltechnology by others, or the presentation software module 175 may passthe information to a presentation software mobile app 195 running in amobile computer/mobile smartphone 190, conventional technology byothers. The presentation software module 175 may alternatively pass theinformation to an electronic billboard, such as, for example, may beoperated by a governmental or commercial entity, and visible to thepublic.

The information passed to the end user may include any of theinformation types held in the database of analyzed information 170,optionally including actionable information and/or recommendationsrelevant to the specific end-user, based on his/her health profile.

In another embodiment of the system, the end-user devices (stationarycomputer 180 and/or mobile computer/mobile smartphone 190 contain airpollution sensor stations 145, 150, built by others may alternatively beused to send data to the database of L0 and L1 data 160. The sensorstations 150 deployment can be on bicycles, balloons, pedestriantransportation, drones, or any other conventional mobile platforms. Thepresentation browser-based Web-application (in computer 180) orpresentation software mobile app (in mobile device 190) sends airpollution measurement data as feedback to the system 240, 245, which isthen stored in the database of L0 and L1 data 160. Such data is thenincluded in the next scheduled or ad hoc round of analysis, and servesto improve the quality of local representation of air pollutioninformation. Additionally, handheld platform 298, which may comprise acomputer 180 or smartphone or tablet device 190 may be deployed in anyambient environment by a system user 297 where in the air pollutionobservation data and any other ambient environment data may be deliveredto data storage 160.

The constellation of satellites is designed to deliver global airpollution data in time increments recognized by the marketplace asreal-time or near-real-time. Cost to deliver is minimized while data“freshness” is maximized. Referring to FIG. 2, in one embodiment, theconstellation consists of a total of eight satellite orbital planes 293around the earth 286 with three satellites 100 with sensor stations perplane, and two spares, for a total of twenty-six satellites. The orbitalplanes are evenly distributed around the earth and arranged insun-synchronous orbits at an altitude of approximately eight hundred km.In other embodiments, the number of orbital planes may be different, andnumber of satellites in each orbital plane may also be different.

The system's initial satellite-based sensor instruments providemonitoring and delivery of data on air pollution components, such asozone, oxides of sulfur, oxides of nitrogen, carbon monoxide, andaerosols. The system is supplemented by additional satellites over thelifetime of the system. Additional air pollution constituent sensors andanalytical capabilities are added as satellites launched later are addedto the constellation.

Referring to FIG. 3., each satellite 300 monitors atmospheric pollutantsfrom ground level through the stratosphere. Multi-spectral sensorinstrument packages 310, monitor atmospheric trace gases and aerosols inthe ultra-violet, visible, near-infrared, short-wave infrared andthermal-infrared bands through receiving optics 315. This spectrum ofbands enables both day-time and night-time monitoring of atmosphericpollutants.

A coverage is the sensing area on the surface of the earth over whichthe satellite passes as it moves over the surface of the earth 305 alonga ground track 340. A coverage swath (or swath) is the sensing widthcomponent of the coverage In one embodiment, each satellite has twoswaths for its sensors 330, 335,where the swaths are approximatelyequally divided, with some overlap.

Each satellite is equipped with an optical or radio-frequency sounder320 which sends optical or radio-frequency signals directly orindirectly down to the ground and reads and stores the returned echodata received along the optical or radio-frequency beam centerline 325.This device provides additional data to the air pollution data,contributing to a three-dimensional characterization of the airpollution data.

In one embodiment,the two swaths are identical and the total swath isevenly divided 330, 335.

Referring to FIG. 4, in another embodiment, the two swaths aredifferent. In this case, as before, each satellite 300 monitorsatmospheric pollutants from ground level through the stratosphere.Multi-spectral sensor instrument packages 310 monitor atmospheric tracegases and aerosols through receiving optics 315. Each satellite isequipped an optical or radio-frequency sounder 320 which sends opticalor radio-frequency signals directly or indirectly down to the ground andreads and stores the returned echo data received along the optical orradio-frequency beam centerline 325. However in this embodiment, twoswaths of differing widths are used, to enable both dedicated airpollution monitoring as well as special event monitoring. A broad swathsensor, for dedicated air pollution monitoring, has a swath in excess ofone thousand km 405 and provides a revisit time of one hour or less overany part of the earth's surface. The narrow swath sensor, for specialevents (e.g. volcanic eruptions, forest fires, etc.) covers a swath inexcess of three hundred km 410 and is selectable to one of three regionscovering the total broad swath sensor coverage. Each sensor has a groundsampling distance that enables high fidelity resolution. Each sensorprovides 3D image and in particular vertical column height informationof atmospheric trace gases and aerosols from earth s surface through tostratosphere. The combination of sensors with broad and narrow swathsprovides a stereo coverage of the atmospheric columns and unique modelvalidation capability Other embodiments may utilize different selectableratios of wide and narrow swaths to achieve additional functionality.

Air pollution sensor data and other data collected by the individualsatellites is downloaded to the system database. Referring to FIG. 5, inone embodiment of the system, each satellite 100 collects data andperiodically transmits said data by radio communications link 510 to aground communications station 505 on the earth surface 305. This data isthen transferred 515 to commercial services in the Internet 520, andfinally delivered 525 to the database of L0 and L1 data 160.

In another embodiment of the system, each satellite 100 collects dataand periodically transmits said data by radio communications link 527 toanother satellite 526 designed for high-volume data communications,typically, but not exclusively, in geosynchronous orbit around theearth, and therefrom by radio communications link 528 to a groundcommunications station 505 on the earth surface 305. This data is thentransferred 515 to commercial services in the Internet 520, and finallydelivered 525 to the database of L0 and L1 data 160.

A significant source of data for the system is data collected bygovernmental agencies, non-governmental entities, other third-partiesand commercial companies. Referring to FIG. 1, such data is typicallyheld in publicly accessible databases or privately held externaldatabases 155. Such data may be accessible through applicationprogramming interlaces (“API's”) defined by those entities. The systemperiodically or asynchronously transfers such data 168, and stores itunaltered in the database of L0 and L1 data 160. Sources of such datainclude NASA, EPA, and a range of non-U.S. entities which collect airpollution, wind, and weather data through their own data collectionsensor networks.

Some such data may originate from stationary ground station networks ofsensor stations operated by others which are similar to this system'sown 135, 140, or likewise may originate from mobile or marine sensorstation networks operated by others and similar to the system's own 255,260, 270, 275.

In one embodiment of the system, a network of ground-based sensorstations is used to collect local air pollution data Referring to FIG.6, each sensor station package, is comprised of a hermetically sealedsensor station container 600, with flow controls to admit air formeasurement, including an air intake tube 615, an air intake filler 610to remove particulates, and an air conditioning unit to control airtemperature. Additional control equipment include a radio communicationsmodule 620, a computer control module 625 and associated software whichcontrols and coordinates operation of all other equipment in the sensorstation, and data cable with connector 630 for data export, and anelectric power supply module 635 with an electric power cable andconnector 640 to supply the entire sensor station.

Each sensor installment may be conventional technology. A particulatesensor probe 645 external to the hermetically sealed case collects aircontaining particulates for analysis by a particulate analysis sensor650. The sensor station also contains an ozone sensor 655, a carbonmonoxide sensor/analyzer 660, a sulfur dioxide/hydrogen sulfidesensor/analyzer 665, a nitrogen oxide and ammonia sensor/analyzer 670,and a volatile organic compounds sensor/analyzer 675. In one embodimentof the system, other sensors/analyzers 680 may be included, such asradiological sensors. All sensor instruments besides the particulatesensor act on filtered air obtained from inside the hermetically sealedsensor station container 600. Each sensor station may be installedtogether with a standard weather station 605, and collects informationfrom the weather station in conjunction with its own sensors.

In another embodiment of the system a network of ground-based sensorstations is used to collect local air pollution data, where the sensorstations have somewhat limited capabilities requiring little or nomaintenance. Referring to FIG. 7, each such sensor station container 700is sealed and contains a radio communications module 710, power supplymodule 715, a power supply cable and connector 725, a computer controlmodule 720, a data cable and connector 730, a photo-spectrometric airpollution sensor installment 735 and a viewport cleansing system. Thephoto-spectrometric air pollution sensor instrument 735 relies on cleanlight-receiving optics 740 through which it obtains measurements. Theoptics arc protected by means of a glass viewing port 745 to theexternal environment, which may become contaminated or dirty with thepassage of time. The glass viewing port 745 is hydrophobic, and alsonegatively charged to repel particles from its exterior surface. Theglass viewing port 745 is periodically cleaned by means of pressurizedair drawn in by an air pump 750 through an air intake port 755, andpassed through an air delivery tube 760, and sprayed through the airwayrestriction nozzle 765 onto the external surface of the glass viewingport 770, thereby blowing away contamination and dust which may beaccumulated on the surface of the glass viewing port 745.

In another embodiment of the sensor station package, again referring toFIG. 7, the components represented by the photo-spectrometric airpollution sensor instrument 735, the glass viewing port 745, and theviewport cleansing system 750,755,760, 765, 770, is provided as acombined conventional technology 775.

In one embodiment of the system, the ground sensor network comprised ofmultiple sensors 815 within multiple sensor stations 135 is deployed asrepresented abstractly in FIG. 8. The network is comprised of networknodes 815, 135, 140. 810, 805, 800 and data communication lines 205,210, 820, 825. Data is collected in the multiple sensor stations 135,then transmitted 205 to computers serving as local data aggregationnodes 140, then transmitted 210 to computers serving as regional dataaggregation nodes 810, then transmitted 210 to computers serving asnational data aggregation nodes 805, then transmitted 820 finally to aglobal data aggregation node 800 and deposited into the database of L0and L1 data 160 as shown in FIG. 1.

Operational and control data is also transmitted from higher nodallevels to lower levels, such as from the global node 800 selectivelydown to the sensor stations 135 and individual instruments 815, as wellas to nodes in between 140, 810, 805. Sensor station nodes 135 alsotransmit peer-to-peer control data between themselves along peer-to-peerdata communications pathways between sensor stations 825 enabling localcooperation to enhance and adjust data collection rates and sensorinstrument adjustments depending on opportunistic data discoveries byindividual sensor stations.

FIG. 9 illustrates features of the ground network sensor station gridfrom a geospatial perspective. Sensor stations 135 are typicallydeployed in a geospatial sector 900, and transfer 205 their sensor datato a data aggregation node 140. Where there is a known stationary airpollution source 910, or in dense urban areas, the sensor stations aredeployed at a relatively high density, with short distances betweenstations 915. Where there is no known stationary air pollution source,or in rural areas, the sensor stations are deployed at a relatively lowdensity, with greater distances between stations 920.

Referring to FIG. 10, a schematic diagram illustrating a client deviceshowing an example embodiment of a client device that may be used withinthe present invention to provide the data reduction and analysis throughthe system of the present invention. The client device may include manymore or less components than those shown in FIG. 10. However, thecomponents shown are sufficient to disclose an illustrative embodimentfor implementing the present invention.

Air pollution data, wind, and weather data contained in the database ofL0 and L1 data 160 is periodically transferred into the computingdevice, comprising an analytic software module 165. The periodicity ofthis activity may vary in various embodiments of the system, however thetypical periodicity is hourly, enabling the information produced to havean age of one hour or less at ail times. The data reduction and analysissteps may be performed in various different orders, including via aclient device, and the resulting information is transferred 220 to theanalyzed information database 170.

A computing device comprising an analytic software module includes aprocessing unit (CPU) in communication with a mass memory 160, 170 via abus 215, 220. The computing device also includes a power supply, one ormore network interfaces, an audio interface, a display, a keypad, anilluminator, an input/output interface, a haptic interface, and anoptional global positioning systems (GPS) receiver. The power supplyprovides power to the computing device. A rechargeable ornon-rechargeable battery may be used to provide power. The power mayalso be provided by an external power source, such as an AC adapter or apowered docking cradle that supplements and/or recharges a battery.

The computing device may optionally communicate with a base station (notshown), or directly with another computing device. One or more networkinterfaces 215, 220 includes circuitry for coupling the computing deviceto one or more networks, and is constructed for use with one or morecommunication protocols and technologies including, but not limited to,global system for communication (GSM), code division multiple access(CDMA), time division multiple access (TDMA), user datagram protocol(UDP), transmission control protocol/Internet protocol (TCP/IP), SMS,general packet radio service (GPRS), WAP, ultra wide band (UWB), IEEE802.16 Worldwide Interoperability for Microwave Access (WiMax), SIP/RTP,or any of a variety of other wireless communication protocols. Thenetwork interface is sometimes known as a transceiver, transceivingdevice, data transfer, or network interface card (NIC).

A keypad may be implemented and may comprise any input device arrangedto receive input from a user. For example, a keypad may include a pushbutton numeric dial, or a keyboard, or may also include command buttonsthat are associated with selecting and sending images. An illuminatormay provide a status indication and/or provide light, and may remainactive for specific periods of time or in response to events Theilluminator may also cause light sources positioned within a transparentor translucent case of the client device to illuminate in response toactions.

The computing device also comprises an input/output interface forcommunicating with external devices, such as a headset, or other inputor output devices not shown in FIG. 10. Input/output interfaces canutilize one or more communication technologies, such as USB, infrared,Bluetooth∜, or the like

Optional GPS transceivers can determine the physical coordinates of acomputing device on the surface of the Earth, which typically outputs alocation as latitude and longitude values. The GPS transceiver can alsoemploy other geo-positioning mechanisms, including, but not limited to,triangulation, assisted GPS (AGPS), E-OTD, CI, SAI, ETA, BSS or thelike, to farther determine the physical location of the computing deviceon the surface of the Earth. It is understood that under differentconditions, the GPS transceiver can determine a physical location withinmillimeters for the computing device; and in other eases, the determinedphysical location may be less precise, such as within a meter orsignificantly greater distances In one embodiment, however, thecomputing device may through other components, provide other informationthat may be employed to determine a physical location of the device,including for example, a MAC address, IP address, or the like.

The one or more database of L0 and L1 data 160, and of analyzedinformation 170, or the computing device itself may further comprisemass memory. Mass memory includes a RAM, a ROM, and other storage means.Mass memory illustrates another example of computer storage media forstorage of information such as computer readable instructions, datastructures, program modules or other data Mass memory stores a basicinput/output system (“BIOS”) for controlling low-level operation ofcomputing device. The mass memory also stores an operating system forcontrolling the operation of computing device. It will be appreciatedthat this component may include a general purpose operating system suchas a version of UNIX, or LINUX™, or a specialized client communicationoperating system such as Windows Client™, or the Symbian® operatingsystem. The operating system may include, or interface with a Javavirtual machine module that enables control of hardware componentsand/or operating system operations via Java application programs.

Memory further includes one or more data stores, which can be utilizedby the computing device to store, among other things, applicationsand/or other data. For example, data stores may be employed to storeinformation that describes various capabilities of the computing device,including the analytic software module. The information may then beprovided to another device based on any of a variety of events,including being sent as part of a header during a communication, sentupon request, or the like. At least a portion of the capabilityinformation may also be stored on a disk drive or other storage medium(not shown) within the computing device.

Applications may include computer executable instructions which, whenexecuted by computing device, transmit, receive, and/or otherwiseprocess audio, video, images, and enable telecommunication with a clientdevice. Other examples of application programs include modeling systems,alarm modules, validation modules, task managers, transcoders, databaseprograms, word processing programs, security applications, spreadsheetprograms, search programs, and so forth. Applications may furtherinclude search client that is configured to send, to receive, and/or tootherwise process an atmospheric or instrumentation data using any knownor to be known communication protocols. It should be clear that multiplesearch clients may be employed. For example, one search client may beconfigured to enter atmospheric or instrumentation data, where anothersearch client manages results, and yet another search client isconfigured to manage modeling systems, development of the various alarmsor threshold conditions, and the like.

Internal architecture of a computing devices), computing system,computing platform and the like includes one or more processing units,processors, or processing cores, (also referred to herein as CPUs),which interface with at least one computer bus. Also interfacing withthe computer bus are computer-readable medium, or media, networkinterface, memory, e.g., random access memory (RAM), run-time transientmemory, read only memory (ROM), media disk drive interface as aninterface for a drive that can read and/or write to media includingremovable media such as floppy, CD-ROM, DVD, media, display interface asinterface for a monitor or other display device, keyboard interface asinterface for a keyboard, pointing device interface as an interface fora mouse or other pointing device, and miscellaneous other interfaces notshown individually, such as parallel and serial port interfaces and auniversal serial bus (USB) interface.

Memory interfaces with the computer bus so as to provide informationstored in memory to the CPU during execution of software programs suchas an operating system, application programs, device drivers, andsoftware modules that comprise program code, and/or computer executableprocess steps, incorporating functionality described herein, e.g., oneor more of process flows described herein. The CPU first loads computerexecutable process steps from storage, e.g., memory, which may includeone or more databases 160, computer readable storage medium/media,removable media drive, and/or other storage device. The CPU can thenexecute the stored process steps in order to execute the loadedcomputer-executable process steps. Stored data, e.g., data stored by astorage device, can be accessed by CPU during the execution ofcomputer-executable process steps.

Persistent storage, e.g., medium/media, can be used to store anoperating system and one or more application programs. Persistentstorage can also be used to store device drivers, such as one or more ofa digital camera driver, monitor driver, printer driver, scanner driver,or other device drivers, web pages, content files, playlists and otherfiles. Persistent storage can further include program modules and datafiles used to implement one or more embodiments of the presentinvention, e.g., listing selection modules), targeting informationcollection module(s), and listing notification module(s), thefunctionality and use of which in the implementation of the presentinvention are discussed in detail herein.

A network link 215, 220 typically provides information communicationusing transmission media through one or more networks to other devicesthat use or process the information. For example, a network link 215,220 may provide a connection through local network to a host computer orto equipment operated by a Network or Internet Service Provider (ISP)ISP equipment in turn provides data communication services through thepublic, worldwide packet switching communication network of networks nowcommonly referred to as the Internet

A computer called a server host connected to the Internet hosts aprocess that, provides a service in response to information receivedover the Internet. For example, server host hosts a process thatprovides information representing video data for presentation atdisplay. It is contemplated that the components of system can bedeployed in various configurations within other computer systems, e.g.,host and server.

At least some embodiments of the present invention are related to theuse of computer systems for implementing some or all of the techniquesdescribed herein. According to one embodiment, those techniques areperformed by computer system in response to a processing unit executingone or more sequences of one or more processor instructions contained inmemory. Such instructions, also called computer instructions, softwareand program code, may be read into memory from another computer-readablemedium such as a storage device, database 160, 170 or network link.Execution of the sequences of instructions contained in memory causes aprocessing unit to perform one or more of the method steps describedherein In alternative embodiments, hardware, such as ASIC, may be usedin place of or in combination with software Thus, embodiments of thepresent invention are not limited to any specific combination ofhardware and soft ware, unless otherwise explicitly stated herein.

The signals transmitted over a network link and other networks through acommunications interface, carry information to and from the computersystem. The computer system can send and receive information, includingprogram code, through the networks, among others, through network linkand communications interface In an example using the internet, a serverhost transmits program code for a particular application, requested by amessage sent from a computer, through Internet. ISP equipment, localnetwork or communications interface. The received code may be executedby the processor as it is received, or may be stored in memory or in astorage device or other non-volatile storage for later execution, orboth.

Referring to Figure 10, in one embodiment of the system, data recentlydeposited into the database of L0 and L1 data 160 is compared to and conelated with older data, including statically held historical data, by acorrelation software module 1005. This correlation is performed byintroducing the data into a global atmospheric model, performingcalculations to record values of air pollution as correlated with olderdata. Data of specific air pollution components is also cross-correlatedwith data of specific other air pollution components

The resulting correlated data is then passed to a source-correlationmodule 1010, which correlates air pollution data and wind and weatherdata obtained from satellites correlated with similar data obtained fromground-based sensors networks, marine networks, automotive mobilenetworks, and mobile phone/tablet-based sensor networks.

The resulting cross-correlated data is next passed to a geospatialcorrelation module 1015, and associated with geospatial coordinates.

The resulting geospatially correlated data is then geospatially mappedas air pollution value surface contours in a three-dimensionalgeospatial model by the geospatial value surface mapper module 1020.

The resulting air pollution value surface contours are then re-evaluatedby taking wind data factors and weather data factors into account by thewind and weather data correlator 1025.

The resulting modified resulting air pollution value surface contoursare then fed to a forward-predictive global air pollution model 1030,which is run once every hour using the correlated data prepared in thepreceding steps.

The resulting information is then transferred into a four-dimensionalanimation module 1035, which animates the geospatial mapping in threespatial dimensions and a time dimension.

The resulting information is then passed to a health correlation module1040 which contains data representing health-related criteria pertainingto each air pollution component. This module evaluates the informationpassed into it for comparison to the said criteria, and generates airpollution density index values and health-related assessments for eachair pollution component. Should any component exceed certain values, themodule generates alerts and warnings which are then stored for retrievalby any end-user or end-user agent such as a presentation application ormobile app.

The resulting information is then passed to a health-careinformation-fusion module 1045 and compared to and fused with staticallyheld health care information and predictive algorithms stored in thedatabase 120 relevant to each of several health-care disciplines, suchas pulmonary care and skin care. This module also generatesdiscipline-specific actionable health-care information for immediatebenefit to end-users and long-term health benefits.

The resulting geospatially correlated mapping (from 1030),four-dimensional animations (from 1035), and indices and alerts (from1040), and health-care specific recommendations (from 1045) aretransferred 220 to a database of analyzed information 170.

In another embodiment of the system, the data processing and analysispathway encompassed by block 165 is supplemented by an alternativepathway whereby a third party external to the system may obtain of L0and L1 data 160 by means of data pathway 1047, processing the datathrough steps analogous to those comprising block 165, i.e., steps 1005.1010, 1015, 1020, 1025, 1030, 1035, 1040, and 1045, or some subsetthereof comprising step 1048, and deliver the processed and analyzeddata through pathway 1049 as information to database 170.

Referring to FIG. 11, a range of presentation options are provided asservices. The operation, of the software modules illustrated here may bein the order shown in FIG. 11, or in various embodiments, they may be indifferent order.

In one embodiment, bulk information is transferred 225 from the databaseof analyzed information 170 to the information presentation softwaremodule 175, prepared for delivery by the presentation informationtransfer packaging module, the information converted into a formatdefined by the system's application programming interface (“API”) 1145,and transferred 250 to an external entity which may use the informationfor presentation in its own software, in Web-based, mobile, or otherformats of its own. Such transfers may be periodically scheduled, e.g.,hourly, or on an ad hoc basis.

In another embodiment, a Web-based application operated by a directsystem end-user sends a request for presentation information 1105 to theinformation presentation software module 175. In turn the informationpresentation software module 175 sends an information request to thedatabase of transformed information 170. The information returned ispassed through one or more of a series of preparation modules 1120,1125, 1130, 1135, 1140, and 1145 operated in an order appropriate forthe specific information request, and transferred 230 to thebrowser-based Web-application 185 and presented to the end-user on thedisplay screen. In this sequence, the information transferred 225 fromthe database of analyzed information 170 is formatted for use by theinformation preparation and formatting software module 1120, theninserted into a geospatial mapping framework 1125. Supplementalinformation which is non-geospatial in nature but rather infographic innature is prepared by the infographic information assembly softwaremodule 1130. The display page assembly module 1135 obtains a static pageframework stored in the database of analyzed information 170, andassembles a page description in hyper-text markup language (“HTML”), andinserts the geospatial information. The infographic overlay assemblymodule 1140 modifies this page description by overlaying the infographicinformation, if any, obtained from the infographic information assemblysoftware module 1130, if any, and generates a final version of the HTMLfile. Finally the presentation information transfer packaging module1145 prepares the file for transfer, by compressing it and addingappropriate header information for transfer using conventional transfercontrol protocol/Internet protocol (TCP/IP). The file is thentransferred 230 to the browser-based Web-application 185 forpresentation. The information transferred and presented may contain airpollution information in geospatial format, as well as air pollutioninformation in infographic format, as well as alerts and recommendationsfor specific actions appropriate to the location of the end-user.

In another embodiment, a mobile app 195 operated by a direct systemend-user sends a request for presentation information 1115 to theinformation presentation software module 175. In turn the informationpresentation software module 175 sends an information request to thedatabase of analyzed information 170. The information returned is passedthrough one or more of a series of preparation modules 1120, 1125, 1130,1135, 3140, and 1145 operated in an order appropriate for the specificinformation request, and transferred 235 to the presentation softwaremobile app 195 and presented to the end-user on the display screen. Inthis sequence, the information retrieved 230 from the database ofanalyzed information 170 is formatted for use by the informationpreparation and formatting software module 1120, then inserted into ageospatial mapping framework 1125. Supplemental information which isnon-geospatial in nature but rather infographic in nature is prepared bythe infographic information assembly software module 1130. The displaypage assembly module 1135 obtains a size-responsive static pageframework suitable for a mobile device display stored in the database ofanalyzed information 170, and assembles a page description in hyper-textmarkup language (“HTML”), and inserts the geospatial information. Theinfographic overlay assembly module 1140 modifies this page descriptionby overlaying the infographic information, if any, obtained from theinfographic information assembly software module 1130, if any, andgenerates a final version of the HTML file. Finally the presentationinformation transfer packaging module 1145 prepares the file fortransfer, by compressing it and adding appropriate header informationfor transfer using conventional transfer control protocol/Internetprotocol (TCP/IP). The file is then transferred 235 to the mobile app195 for presentation. The information transferred and presented maycontain air pollution information in geospatial format, as well as airpollution information in infographic format, as well as alerts andrecommendations for specific actions appropriate to the location of theend-user.

Referring to FIG. 11, the browser-based Web application 185 is capableof presenting air pollution information in geospatial format, and alsoin infographic format. The browser-based Web application 185 is capableof taking, and later editing, information from an end-user, and locallystoring the end-user's health information formatted as a health profile.The browser-based Web application 185 references this health profile toactivate context-sensitive alerts and advisory messages originating fromthe database of analyzed information 170 which are applicable to thespecific end-user.

Referring to FIG. 11 the presentation software mobile app 195 is capableof presenting air pollution information in geospatial format, and alsoin Infographic formal. The presentation software mobile app 195 iscapable of taking, and later editing, information from an end-user, andlocally storing the end-user's health information formatted as a healthprofile. The presentation software mobile app 195 references this healthprofile to activate context-sensitive alerts and advisory messagesoriginating from the database of analyzed information 170 which areapplicable to the specific end-user.

For the purposes of this disclosure a module is a software, hardware, orfirmware (or combinations thereof) system, process or functionality, orcomponent thereof, that performs or facilitates the processes, features,and/or functions described herein (with or without human interaction oraugmentation). A module can include sub-modules. Software components ofa module may be stored on a computer readable medium for execution by aprocessor. Modules may be integral to one or more servers, or be loadedand executed by one or more servers. One or more modules may be groupedinto an engine or an application.

This disclosure provides illustrative nonlimiting embodiments includingan atmospheric information network a group of low earth orbit satellitescarrying atmospheric air pollution observation instruments and sensorsproviding global coverage of the earth, one or more unmanned aerialvehicles carrying atmospheric air pollution observation instruments, airsampling instruments, and sensors, and one or more conventional aircraftor manned aerial vehicles carrying atmospheric air pollution observationinstruments, air sampling instruments, and sensors; and one or moreterrestrial (ground-based) networks of sensor stations, each stationcontaining atmospheric air pollution observation instruments, airsampling instruments, sensors; and one or more terrestrial-vehicle-basedsensor stations, each station containing atmospheric air pollutionobservation instruments, air sampling instruments, sensors; and one ormore human-carried mobile sensor stations, each carrying air samplinginstruments and sensors; and a ground-based network of data telemetrytransceiver antenna stations, through which space-based data iscollected from the aforementioned satellites; and a data telemetrysystem for passing low earth orbit satellite-originated data through oneor more geostationary satellites and re-transmitting said data to theground-based data telemetry network, and one or more data stores; andsoftware to manage ingestion of atmospheric air pollution data into thedata store s); and one or more data modeling software systems forcorrelation, analysis of collected data, data fusion, and conversion toactionable information, also may include one or more data modelingsoftware systems for forward-prediction of air pollution; softwaresystems for preparation of presentation of air pollution data incomputer-display able formats; and presentation software forpresentation of air pollution data in computer-displayable formats; andone or more Application Programming Interfaced) (APIs) for data exchangewith atmospheric information networks and data stores operated byothers.

Other nonlimiting embodiments provide an atmospheric information networkthrough which data is moved from sensed location(s), analyzed, andprepared for presentation to presentation software and hardwarelocations, in real-time or near realtime; and stored in format(s)suitable for real-time or near-real-time access and/or presentation.

Still other embodiments provide an atmospheric information analysissystem that correlates air pollution information with other atmosphericinformation such as wind information, insolation, and thermalinformation: and correlates air pollution information with staticcriteria producing actionable information for end users. The network mayalso enable third parties to retrieve from, analyze, and return analyzeddata to the data store facility. Software associated with the data storefacility may integrate third party sourced data with other data presentin the data store. Other embodiments of the atmospheric informationnetwork provide for data conformation to international data standardsfor air pollution data.

Other embodiments provide a network-based system for providing airpollution observations and information derived therefrom, where thesystem includes a plurality of low earth orbit satellites carryingatmospheric air pollution observation instruments providing globalcoverage of the earth to obtain air pollution observation data; aplurality of manned or unmanned aerial vehicles carrying atmospheric airpollution observation instruments to obtain air pollution observationdata; a plurality of terrestrial sensor stations containing atmosphericair pollution observation instruments to obtain air pollutionobservation data; a data storage facility to store the obtained airpollution data; data modeling software for analysis and conversion ofatmospheric air pollution observations into end-user data andinformation; and a data delivery platform for providing end-user dataand information.

Additionally the system may provide that the low-earth orbit, satellitesare operated in sun-synchronous positions. The low-health orbitsatellites, the aerial vehicles and the terrestrial sensor stations mayacquire weather data along with the air pollution observation data. Atleast one of the low-earth satellites may provide high-volume datacommunications. The terrestrial sensor stations containing atmosphericair pollution observation instruments may be handheld platforms that mayobtain and receive air pollution observation data. Sensor stationscontaining atmospheric air pollution observation instruments may bemotorized terrestrial vehicles or aquatic-surface based crafts. Variouscommunication transmission links to provide air pollution observationdata to the data storage facility. The data modeling software providesforward-prediction of air-pollution. The system may include a softwaremodule for displaying computer presentation of air pollutionobservations. The data delivery platform may be a software applicationservice.

Another nonlimiting embodiment is a method of providing air pollutionobservation services to an end-user that includes acquiring airpollution observation data from a group of low earth orbit satellitescarrying atmospheric air pollution observation instruments and sensorsproviding global coverage of the earth, acquiring air pollutionobservation data from a plurality of manned or unmanned aerial vehiclescarry ing atmospheric air pollution observation instruments, acquiringair pollution observation data from a plurality of terrestrial sensorstations containing atmospheric air pollution observation instruments,storing the obtained air pollution data in a data storage facility,analyzing the acquired data with data modeling software to obtainatmospheric air pollution end-user specific data, and delivering theend-user data to an end-user platform.

In other embodiment the method may include operating the low-healthorbit satellites in sun-synchronous positions, or acquiring weather datausing the low-earth orbit satellites, the aerial vehicles and theterrestrial sensor stations. The method may provide high-volume datacommunications with at least one of the low earth orbit satellites oracquiring air pollution data from a handheld sensor station or mobiledevice that may obtain and receive air pollution observation data.Atmospheric air pollution observations may be acquired from sensorstations fixed to a motorized terrestrial vehicle or water craft.Embodiments of the method may provide for delivery of forward-predictionof air-pollution conditions to an end-user as well as a computerpresentation of air pollution observations Software application serviceswith formatted data may be delivered to the end-user platform.

In yet more nonlimiting embodiments a computer program product embodiedin non-transitory computer readable media is provided, the computerprogram product adapted to execute a process to provide air pollutionobservation data and information for delivery to an end-user platform,the process comprising processing data acquired from a plurality ofsensors associated with a plurality of low earth orbit satellitescarrying atmospheric air pollution observation instruments, a pluralityof manned or unmanned aerial vehicles carrying atmospheric air pollutionobservation instruments to obtain air pollution observation data, and aplurality of terrestrial sensor stations containing atmospheric airpollution observation instruments to obtain air pollution observationdata; the process further comprising storing the obtained air pollutiondata in a data storage facility; processing the air pollution datathrough data modeling software for analysis and conversion into end-userdata and information; and delivering the end-user data and informationto the end-user platform.

Other embodiments of the program include end-user data and informationthat is personalized to an end-user. The end-user data and informationmay be delivered over a secure network. Processing the air pollutiondata may include incorporating atmospheric observation data fromgovernmental and third-party sources. End-user platforms may include,but are not limited to software application programs, web applications,stand-alone applications, mobile-device applications, and ApplicationProgramming Interfaces. The end-user specific data and information maybe formatted to display in a geospatial mapping presentation. End-userspecific data and information may be delivered in response to a deliveryrequest from an end-user platform. The process of the computer programproduct may deliver air pollution information in geospatial format, ininfographic format, as information-based alerts, as recommendationsappropriate for end-user specific locations, or as recommendationsappropriate to end-user specific requests. The computer program productmay acquire air pollution data from a sensor associated with theend-user platform.

Other nonlimiting embodiments disclosed herein include a method ofproviding air pollution observations to an end-user platform from anetwork database that includes storing authorization information andend-user platform specific information within the end-user platform andstoring the authorization information and end-user platform specificinformation within a network database. If the authorization informationstored in the network database agrees with the authorization informationprovided in a request from the end-user platform then end-user-specificair pollution data and information is delivered to the end-user platformfrom the network database and the end-user specific air pollution dataand information is updated on the end-user platform.

Other embodiments of the method provide that air pollution observationsin the network database arc acquired from a plurality of low earth orbitsatellites carrying atmospheric air pollution observation instruments, aplurality of manned or unmanned aerial vehicles carrying atmospheric airpollution observation instruments, and a plurality of terrestrial sensorstations containing atmospheric air pollution observation instruments.The acquired air pollution data in the network database may be processedthrough data modeling software for analysis and conversion intoend-user-specific data and information The air pollution observations inthe network database may be acquired from governmental, non-governmentaland third-party sources. The end-user specific platform informationdelivered may be an end-user health profile. The delivered end-userspecific air pollution observations may be context specific informationfrom the network database that is based on an end-user health profile.Context specific information based on an end-user health profile storedmay be displayed on the end-user platform along with air pollutionobservations delivered from the network database. Air pollutionobservations may be delivered to the end-user platform on a regularperiodic basis. Delivering end-user specific air pollution observationsmay also include forward predictions of future atmospheric and airpollution conditions. A sensor associated with the end user platform mayprovide air pollution observation data to the network database.

Those skilled in the art will recognize that the methods and systems ofthe present invention may be implemented in many manners and as such arenot to be limited by the foregoing exemplary embodiments and examples.Furthermore, the embodiments of methods presented and described asfigures or charts in this disclosure arc provided by way of example inorder to provide a more complete understanding of the technology.Disclosed methods are not limited to the operations and logical flowpresented herein. Alternative embodiments are contemplated in which theorder of the various operations is altered and in which sub-operationsdescribed as being part of a larger operation are performedindependently. While various embodiments have been described forpurposes of this disclosure, such embodiments should not be deemed tolimit the teaching of this disclosure to those embodiments. Variouschanges and modifications may be made to the elements and operationsdescribed above to obtain a result that remains within the scope of thesystems and processes described in this disclosure.

1-19. (canceled)
 20. A method of providing air pollution observations toan end-user platform from a network database, comprising; a. storingauthorization information and end-user platform specific informationwithin the end-user platform; b. storing the authorization informationand end-user platform specific information within a network database; c.if the authorization information stored in the network database agreeswith the authorization information provided in a request from theend-user platform then; I. deliver end-user-specific air pollution dataand information to the end-user platform from the network database; andII. updating end-user specific air pollution data and information on theend-user platform.
 21. The method of claim 20 wherein the air pollutionobservations in the network database are acquired from a plurality oflow earth orbit satellites carrying atmospheric air pollutionobservation instruments, a plurality of manned or unmanned aerialvehicles carrying atmospheric air pollution observation instruments, anda plurality of terrestrial sensor stations containing atmospheric airpollution observation instruments.
 22. The method of claim 20 whereinthe acquired air pollution data in the network database are processedthrough data modeling software for analysis and conversion intoend-user-specific data and information.
 23. The method of claim 20wherein air pollution observations in the network database are acquiredfrom governmental, non-governmental and third-party sources.
 24. Themethod of claim 20 wherein end-user specific platform information is anend-user health profile.
 25. The method of claim 20 wherein thedelivered end-user specific alr pollution observations further activatecontext specific information from the network database based on anend-user health profile.
 26. The method of claim 20 further comprisingdisplaying context specific information based on an end-user healthprofile stored on the end-user platform and air pollution observationsdelivered from the network database.
 27. The method of claim 20 whereinthe air pollution observations are delivered to the end-user platform ona regular periodic basis.
 28. The method of claim 20 wherein deliveringend-user specific air pollution observations further comprises providingforward predictions of future atmospheric and air pollution conditions.29. The method of claim 20 further comprising acquiring air pollutionobservation data from a sensor associated with the end-user platform.